drift-estimation | Drift estimation

by qnano C++ Version: V1.2 License: No License

X-Ray Key Features Code Snippets Community Discussions Vulnerabilities Install Support

kandi X-RAY | drift-estimation Summary

drift-estimation is a C++ library. drift-estimation has no bugs, it has no vulnerabilities and it has low support. You can download it from GitHub.

Drift estimation

Support

Quality

Security

License

Reuse

Support

drift-estimation has a low active ecosystem.

It has 2 star(s) with 1 fork(s). There are 3 watchers for this library.

It had no major release in the last 12 months.

drift-estimation has no issues reported. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of drift-estimation is V1.2

Quality

drift-estimation has no bugs reported.

Security

drift-estimation has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

License

drift-estimation does not have a standard license declared.

Check the repository for any license declaration and review the terms closely.

Without a license, all rights are reserved, and you cannot use the library in your applications.

Reuse

drift-estimation releases are available to install and integrate.

Installation instructions, examples and code snippets are available.

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drift-estimation Key Features

No Key Features are available at this moment for drift-estimation.

drift-estimation Examples and Code Snippets

No Code Snippets are available at this moment for drift-estimation.

Community Discussions

No Community Discussions are available at this moment for drift-estimation.Refer to stack overflow page for discussions.

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install drift-estimation

On Windows, install cmake and make sure it is available in the path. Then, run build_windows.bat
On Linux (tested on Ubuntu 20.04): Install CUDA from the nVidia website. Install cmake and use "cmake .", followed by "make" in the repository root. This should build ./bin/release/libdme.so dme_example.py should now run without errors.
On MacOS, CUDA is no longer supported by nVidia, so only the CPU version can be used. Thanks to Duncan Ryan for help getting the GCC build working and confirming it runs on MacOS!

Support

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

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